The Sixth Workshop on Syntax, Semantics and Structure in Statistical
Translation (SSST-6) seeks to build on the foundations established in
the first five SSST workshops, which brought together a large number
of researchers working on diverse aspects of structure, semantics and
representation in relation to statistical machine translation. Its
program each year has comprised high-quality papers discussing current
work spanning topics including: new grammatical models of translation;
new learning methods for syntax- and semantics-based models; formal
properties of synchronous/transduction grammars (hereafter S/TGs);
discriminative training of models incorporating linguistic features;
using S/TGs for semantics and generation; and syntax- and
semantics-based evaluation of machine translation.

The need for structural mappings between languages is widely
recognized in the fields of statistical machine translation and spoken
language translation, and there is a growing consensus that these
mappings are appropriately represented using a family of formalisms
that includes synchronous/transduction grammars and their
tree-transducer equivalents. To date, flat-structured models, such as
the word-based IBM models of the early 1990s or the more recent
phrase-based models, remain widely used. But tree-structured mappings
arguably offer a much greater potential for learning valid
generalizations about relationships between languages.

Within this area of research there is a rich diversity of approaches.
There is active research ranging from formal properties of S/TGs to
large-scale end-to-end systems. There are approaches that make heavy
use of linguistic theory, and approaches that use little or none.
There is theoretical work characterizing the expressiveness and
complexity of particular formalisms, as well as empirical work
assessing their modeling accuracy and descriptive adequacy across
various language pairs. There is work being done to invent better
translation models, and work to design better algorithms. Recent years
have seen significant progress on all these fronts. In particular,
systems based on these formalisms are now top contenders in MT
evaluations.

At the same time, SMT has seen a movement toward semantics over the
past few years, which has been reflected at recent SSST workshops,
including the last edition which had semantics for SMT as a special
theme. The issues of deep syntax and shallow semantics are closely
linked and SSST-6 encourages submissions on semantics for MT in a
number of directions, including semantic role labeling (SRL) for SMT,
WSD for SMT and in particular, semantics for MT evaluation. In order
to emphasize the need to evaluate MT in a way that properly assesses
preservation of structure and semantics, SSST-6 is highlighting
Semantic MT Evaluation as a special workshop theme.

Ongoing work suggests that MT evaluation is improved by generalizing
across similar word meanings (Zhou et al., 2006; Apidianaki et al,
2009; Snover et al., 2009; Denkowski and Lavie, 2010), and explicitly
modeling preservation of meaning with textual entailment (Padó et al.
2009), or semantic frames (Lo and Wu, 2011). However, crucial
questions such as what frameworks are best suited to measure MT
quality in general, and the impact of semantic modeling in MT
evaluation remain unanswered. With this year's special theme, we seek
to bring together researchers working on semantics and on translation
evaluation in order to encourage cross-pollination of ideas, share
insights into the needs of MT evaluation and what current developments
in semantics have to offer. We particularly encourage the submission
of papers addressing the following issues related to semantics-driven
evaluation of MT:

Camera ready final versions will be accepted on or before 23 May 2012 in
PDF or Postscript formats via the START system at https://www.softconf.com/acl2012/ssst-6/.
Papers should follow the ACL 2012 camera ready length and
formatting requirements for long papers of eight (8) pages of content
with two (2) additional pages of references, found at http://www.acl2012.org/call/sub01.asp.